Michael Clark

Introduction It’s been nearly four years since I first summarized the state of deep learning (DL) for tabular data, and about three years since my follow-up post.

My book, Models Demystified: A Practical Guide from Linear Regression to Deep Learning, co-authored with Seth Berry, is now published!

As with the last post on class imbalance, this is a resurrection of sorts.

This post began around two years ago and was initially intended for the Strong Analytics blog, but for various reasons never came to fruition.

Update Among many things that have happened recently, I’ve become a father to a beautiful baby girl, and written a book to come out this year (2025).

Book in progess TLDR: https://m-clark.github.io/book-of-models Been a long time since I posted.

It’s been a bit so thought I’d force myself to post a couple things I’ve played around with, or that aren’t ready yet for a full post, or won’t be one.

Introduction NB: This post was revisited when updating the website early 2025, and some changes were required.

NB: This post was revisited when updating the website early 2025, and some changes were required.

NB: This post was revisited when updating the website early 2025, and some changes were required.

Introduction In a previous post, I offered a summary of several articles that came out over the summer of 2021 regarding the application of deep learning (DL) methods to tabular data.

A co-worker passed along a recent article (Dar et al. 2021) on the topic of double descent in machine learning.

Motivation I’ve been a little perplexed at the lack of attention of deep learning (DL) toward what I consider to be ‘default’ data in my world, often referred to as tabular data, where typically we have a two dimensional input of observations (rows) and f…

NB: This post was revisited when updating the website early 2025, and some changes were required.

NB: This post was revisited when updating the website early 2025, and some changes were required.

New Book I’ve completed a new bookdown document, Models by Example, that converts most of the code from my Miscellaneous R repo.

NB: This post was revisited when updating the website early 2025, and some changes were required.

Introduction In R there are many tools available to help you dive in and explore your data.

NB: This post was revisited when updating the website early 2025, and some changes were required.

NB: This post was revisited when updating the website early 2025, and some changes were required.